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Nonparametric entropy-based tests of independence between stochastic processes

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  • Fernandes, Marcelo

Abstract

This paper develops nonparametric tests of independence between two stationary stochastic processes. The testing strategy boils down to gauging the closeness between the joint and the product of the marginal stationary densities. For that purpose, I take advantage of a generalized entropic measure so as to build a class of nonparametric tests of independence. Asymptotic normality and local power are derived using the functional delta method for kernels, whereas finite sample properties are investigated through Monte Carlo simulations.

Suggested Citation

  • Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    • Handle: RePEc:fgv:epgewp:413
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    2. George Kapetanios, 2007. "A Test for Serial Dependence Using Neural Networks," Working Papers 609, Queen Mary University of London, School of Economics and Finance.
    3. Paulo Ferreira, 2012. "Testing serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece," CEFAGE-UE Working Papers 2012_24, University of Evora, CEFAGE-UE (Portugal).
    4. Menezes, Rui & Dionísio, Andreia & Hassani, Hossein, 2012. "On the globalization of stock markets: An application of Vector Error Correction Model, Mutual Information and Singular Spectrum Analysis to the G7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 369-384.
    5. Atanu Biswas & Maria Carmen Pardo & Apratim Guha, 2014. "Auto-association measures for stationary time series of categorical data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 487-514, September.
    6. Paulo Ferreira & Andreia Dion�sio, 2014. "Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece," Applied Financial Economics, Taylor & Francis Journals, vol. 24(5), pages 319-331, March.
    7. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Testing Serial Independence via Density-Based Measures of Divergence," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 627-641, September.
    8. George Kapetanios, 2007. "A Test for Serial Dependence Using Neural Networks," Working Papers 609, Queen Mary University of London, School of Economics and Finance.

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